{"id":"W1969973065","doi":"10.1186/1471-2105-15-11","title":"kruX: matrix-based non-parametric eQTL discovery","year":2014,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Biotechnology and Biological Sciences Research Council","keywords":"Expression quantitative trait loci; Parametric statistics; Computer science; Test statistic; Statistical hypothesis testing; Robustness (evolution); Quantitative trait locus; Multiple comparisons problem; Outlier; Computational biology; Biology; Genetics; Mathematics; Statistics; Artificial intelligence; Genotype; Single-nucleotide polymorphism; Gene","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009203346,0.001649902,0.002098197,0.002332838,0.001112636,0.002736554,0.003548405,0.001484604,0.02749328],"category_scores_gemma":[0.0369892,0.001337504,0.003712884,0.002053182,0.001544733,0.00158494,0.004362438,0.002880051,0.006689134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007539579,"about_ca_system_score_gemma":0.002553764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001803252,"about_ca_topic_score_gemma":0.002831777,"domain_scores_codex":[0.995234,0.002237177,0.000310853,0.001174459,0.0008397005,0.0002038239],"domain_scores_gemma":[0.9822717,0.01485873,0.0006574944,0.001500303,0.00050093,0.0002108496],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003010427,0.0004696978,0.02700401,0.004156012,0.003203469,0.00227357,0.00123163,0.1049198,0.01786273,0.08215167,0.1401117,0.6136052],"study_design_scores_gemma":[0.001100186,0.0004609183,0.006380652,0.0002237677,0.0004474238,0.001611572,0.0002094515,0.7733243,0.01227617,0.1516523,0.0520663,0.0002469241],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008615796,0.0004705949,0.9328811,0.0004104214,0.0001627181,0.0003284745,0.007073079,0.04883029,0.001227596],"genre_scores_gemma":[0.09351169,0.0002862494,0.8852733,0.0007632655,0.00009976429,0.002114051,0.008695201,0.006561392,0.002695187],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02749328,"threshold_uncertainty_score":0.09197414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01105009168094682,"score_gpt":0.2604783079881021,"score_spread":0.2494282163071553,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}